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Bipartite Network Projection
Bipartite network projection is an extensively used method for compressing information about bipartite networks. Since the one-mode projection is always less informative than the original bipartite graph, an appropriate method for weighting network connections is often required. Optimal weighting methods reflect the nature of the specific network, conform to the designer's objectives and aim at minimizing information loss. Background Bipartite networks are a particular class of complex networks, whose nodes are divided into two sets X and Y, and only connections between two nodes in different sets are allowed. For the convenience of directly showing the relation structure among a particular set of nodes, bipartite networks are usually compressed by one-mode projection. This means that the ensuing network contains nodes of only either of the two sets, and two X (or, alternatively, Y) nodes are connected only when they have at least one common neighboring Y (or, alternatively, X) ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bipartite Graph
In the mathematical field of graph theory, a bipartite graph (or bigraph) is a graph whose vertices can be divided into two disjoint and independent sets U and V, that is every edge connects a vertex in U to one in V. Vertex sets U and V are usually called the ''parts'' of the graph. Equivalently, a bipartite graph is a graph that does not contain any odd-length cycles. The two sets U and V may be thought of as a coloring of the graph with two colors: if one colors all nodes in U blue, and all nodes in V red, each edge has endpoints of differing colors, as is required in the graph coloring problem.. In contrast, such a coloring is impossible in the case of a non-bipartite graph, such as a triangle: after one node is colored blue and another red, the third vertex of the triangle is connected to vertices of both colors, preventing it from being assigned either color. One often writes G=(U,V,E) to denote a bipartite graph whose partition has the parts U and V, with E denoting ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Projection (relational Algebra)
In relational algebra, a projection is a unary operation written as \Pi_( R ), where R is a relation and a_1,...,a_n are attribute names. Its result is defined as the set obtained when the components of the tuples in R are restricted to the set \ – it ''discards'' (or ''excludes'') the other attributes. In practical terms, if a relation is thought of as a table, then projection can be thought of as picking a subset of its columns. For example, if the attributes are (name, age), then projection of the relation onto attribute list (age) yields – we have discarded the names, and only know what ages are present. Projections may also modify attribute values. For example, if R has attributes a, b, c, where the values of b are numbers, then \Pi_( R ) is like R, but with all b-values halved.http://www.csee.umbc.edu/~pmundur/courses/CMSC661-02/rel-alg.pdf ''See Problem 3.8.B on page 3'' Related concepts The closely related concept in set theory (see: projection (set theory)) differs ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Complex Network
In the context of network theory, a complex network is a graph (network) with non-trivial topological features—features that do not occur in simple networks such as lattices or random graphs but often occur in networks representing real systems. The study of complex networks is a young and active area of scientific research (since 2000) inspired largely by empirical findings of real-world networks such as computer networks, biological networks, technological networks, brain networks, climate networks and social networks. Definition Most social, biological, and technological networks display substantial non-trivial topological features, with patterns of connection between their elements that are neither purely regular nor purely random. Such features include a heavy tail in the degree distribution, a high clustering coefficient, assortativity or disassortativity among vertices, community structure, and hierarchical structure. In the case of directed networks these feat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bipartite Network Projection
Bipartite network projection is an extensively used method for compressing information about bipartite networks. Since the one-mode projection is always less informative than the original bipartite graph, an appropriate method for weighting network connections is often required. Optimal weighting methods reflect the nature of the specific network, conform to the designer's objectives and aim at minimizing information loss. Background Bipartite networks are a particular class of complex networks, whose nodes are divided into two sets X and Y, and only connections between two nodes in different sets are allowed. For the convenience of directly showing the relation structure among a particular set of nodes, bipartite networks are usually compressed by one-mode projection. This means that the ensuing network contains nodes of only either of the two sets, and two X (or, alternatively, Y) nodes are connected only when they have at least one common neighboring Y (or, alternatively, X) ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Adjacency Matrix
In graph theory and computer science, an adjacency matrix is a square matrix used to represent a finite graph. The elements of the matrix indicate whether pairs of vertices are adjacent or not in the graph. In the special case of a finite simple graph, the adjacency matrix is a (0,1)-matrix with zeros on its diagonal. If the graph is undirected (i.e. all of its edges are bidirectional), the adjacency matrix is symmetric. The relationship between a graph and the eigenvalues and eigenvectors of its adjacency matrix is studied in spectral graph theory. The adjacency matrix of a graph should be distinguished from its incidence matrix, a different matrix representation whose elements indicate whether vertex–edge pairs are incident or not, and its degree matrix, which contains information about the degree of each vertex. Definition For a simple graph with vertex set , the adjacency matrix is a square matrix such that its element is one when there is an edge from vertex to ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Matching (graph Theory)
In the mathematical discipline of graph theory, a matching or independent edge set in an undirected graph is a set of edges without common vertices. Finding a matching in a bipartite graph can be treated as a network flow problem. Definitions Given a graph a matching ''M'' in ''G'' is a set of pairwise non-adjacent edges, none of which are loops; that is, no two edges share common vertices. A vertex is matched (or saturated) if it is an endpoint of one of the edges in the matching. Otherwise the vertex is unmatched (or unsaturated). A maximal matching is a matching ''M'' of a graph ''G'' that is not a subset of any other matching. A matching ''M'' of a graph ''G'' is maximal if every edge in ''G'' has a non-empty intersection with at least one edge in ''M''. The following figure shows examples of maximal matchings (red) in three graphs. : A maximum matching (also known as maximum-cardinality matching) is a matching that contains the largest possible number of edges. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Collaborative Filtering
Collaborative filtering (CF) is a technique used by recommender systems.Francesco Ricci and Lior Rokach and Bracha ShapiraIntroduction to Recommender Systems Handbook Recommender Systems Handbook, Springer, 2011, pp. 1-35 Collaborative filtering has two senses, a narrow one and a more general one. In the newer, narrower sense, collaborative filtering is a method of making automatic predictions (filtering) about the interests of a user by collecting preferences or taste information from many users (collaborating). The underlying assumption of the collaborative filtering approach is that if a person ''A'' has the same opinion as a person ''B'' on an issue, A is more likely to have B's opinion on a different issue than that of a randomly chosen person. For example, a collaborative filtering recommendation system for preferences in television programming could make predictions about which television show a user should like given a partial list of that user's tastes (likes or dislikes ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Recommender System
A recommender system, or a recommendation system (sometimes replacing 'system' with a synonym such as platform or engine), is a subclass of information filtering system that provide suggestions for items that are most pertinent to a particular user. Typically, the suggestions refer to various decision-making processes, such as what product to purchase, what music to listen to, or what online news to read. Recommender systems are particularly useful when an individual needs to choose an item from a potentially overwhelming number of items that a service may offer. Recommender systems are used in a variety of areas, with commonly recognised examples taking the form of playlist generators for video and music services, product recommenders for online stores, or content recommenders for social media platforms and open web content recommenders.Pankaj Gupta, Ashish Goel, Jimmy Lin, Aneesh Sharma, Dong Wang, and Reza Bosagh ZadeWTF:The who-to-follow system at Twitter Proceedings of the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Disparity Filter Algorithm Of Weighted Network
Disparity filter . is a network reduction algorithm (a.k.a. graph sparsification algorithm ) to extract the backbone structure of undirected weighted network. Many real world networks such as citation networks, food web, airport networks display heavy tailed statistical distribution of nodes' weight and strength. Disparity filter can sufficiently reduce the network without destroying the multi-scale nature of the network. The algorithm is developed by M. Angeles Serrano, Marian Boguna and Alessandro Vespignani. Overview of other network reduction algorithms and their limitations ''k''-core decomposition ''k''-core decomposition is an algorithm that reduces a graph into a maximal connected subgraph of vertices with at least degree ''k''. This algorithm can only be applied to unweighted graphs. Minimum spanning tree A minimum spanning tree is a tree-like subgraph of a given graph ''G'', in which it keeps all the nodes of graph ''G'' but minimizes the total weight of the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ingredient-flavor Network
In network science, ingredient-flavor networks are networks describing the sharing of flavor compounds of culinary ingredients. In the bipartite form, an ingredient-flavor network consist of two different types of nodes: the ingredients used in the recipes and the flavor compounds that contributes to the flavor of each ingredients. The links connecting different types of nodes are undirected, represent certain compound occur in each ingredients. The ingredient-flavor network can also be projected in the ingredient or compound space where nodes are ingredients or compounds, links represents the sharing of the same compounds to different ingredients or the coexistence in the same ingredient of different compounds. History In 2011, Yong-Yeol Ahn, Sebastian E. Ahnert, James P. Bagrow and Albert-László Barabási [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Food Pairing
Foodpairing, or the non-registered trademarked term food pairing, is a method for identifying which foods go well together from a flavor standpoint. The method is based on the principle that foods combine well with one another when they share key Flavor (taste), flavor components. Foodpairing uses HPLC, gas chromatography and other laboratory methods to analyze food and find chemical components that they have in common. The method aids recipe design and provides new ideas for food combinations, which are theoretically sound on the basis of their Flavor (taste), flavor. It provides possible food combinations, which are solely based on the intrinsic properties of the different food products; these combinations are based on the flavor compounds that are present in the products. It also can result in unusual combinations (e.g. endives in a dessert, white chocolate and caviar, or chocolate and cauliflower). While unusual these combinations are found enjoyable to many people because th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Network Management
Network management is the process of administering and managing computer networks. Services provided by this discipline include fault analysis, performance management, provisioning of networks and maintaining quality of service. Network management software is used by network administrators to help perform these functions. Technologies A small number of accessory methods exist to support network and network device management. Network management allows IT professionals to monitor network components within large network area. Access methods include the SNMP, command-line interface (CLI), custom XML, CMIP, Windows Management Instrumentation (WMI), Transaction Language 1 (TL1), CORBA, NETCONF, and the Java Management Extensions (JMX). Schemas include the Structure of Management Information (SMI), WBEM, the Common Information Model (CIM Schema), and MTOSI amongst others. See also * Application service management * Business service management * Capacity management * Comparison ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
